Evidence map›Paper›PMID 36266635›Full record

ArticleBMC genomics2022

Construction and analysis of sample-specific driver modules for breast cancer.

Yuanyuan Chen, Haitao Li, Xiao Sun

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 51% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 1 country.

Yuanyuan ChenState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, P. R. China.
Haitao LiState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, P. R. China.
Xiao SunState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, P. R. China. xsun@seu.edu.cn.
Nanjing Agricultural University · CNSoutheast University · CNState Key Laboratory of Digital Medical Engineering

Funding

China Postdoctoral Science Foundation 2019M651658National Natural Science Foundation of China 81830053, 61972084
6 · The paper itself

Abstract

backgroundIt is important to understand the functional impact of somatic mutation and methylation aberration at an individual level to implement precision medicine. Recent studies have demonstrated that the perturbation of gene interaction networks can provide a fundamental link between genotype (or epigenotype) and phenotype. However, it is unclear how individual mutations affect the function of biological networks, especially for individual methylation aberration. To solve this, we provided a sample-specific driver module construction method using the 2-order network theory and hub-gene theory to identify individual perturbation networks driven by mutations or methylation aberrations.

resultsOur method integrated multi-omics of breast cancer, including genomics, transcriptomics, epigenomics and interactomics, and provided new insight into the synergistic collaboration between methylation and mutation at an individual level. A common driver pattern of breast cancer was identified from a novel perspective of a driver module, which is correlated to the occurrence and development of breast cancer. The constructed driver module reflects the survival prognosis and degree of malignancy among different subtypes of breast cancer. Additionally, subtype-specific driver modules were identified.

conclusionsThis study explores the driver module of individual cancer, and contributes to a better understanding of the mechanism of breast cancer driven by the mutations and methylation variations from the point of view of the driver network. This work will help identify new therapeutic combinations of gene mutations and drugs in humans.

Indexed as

Gene Regulatory NetworksNeoplasmsEpigenomicsGenomicsHumansMutationPrognosis2-order network theoryCommon driver patternSample-specific driver moduleSample-specific network methodSynergistic collaboration

Identifiers

PMID36266635
PMCPMC9583575
OpenAlexW4306929705

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.